Industrial engineering, operations research, and systems engineering are fields of study intended for individuals who are interested in analyzing and formulating abstract models of complex systems with the intention of improving system performance. Unlike traditional disciplines in engineering and the mathematical sciences, the fields address the role of the human decision-maker as key contributor to the inherent complexity of systems and primary benefactor of the analyses.

ISyE's faculty and staff members strive to provide a world-class educational experience for the Stewart School's undergraduate and graduate students, and to forge long-lasting relationships with ISyE alumni and industry partners. If you have benefited from a connection with an ISyE faculty or staff member, feel free to take a moment to send a thank-you note to that person via this web form.

You can stay in touch with all things ISyE through our news feed, by reading one of our publications, or attending one of our upcoming events. ISyE employs some of the world’s most experienced researchers in their fields who enjoy sharing their perspectives on a wide variety of topics. Our faculty is world-renowned and our students are intellectually curious. Our alumni can be found around the globe in leadership positions within a wide variety of fields.

Analytics and Big Data

ISyE faculty and students are working on theoretical and methodological advances in analytics, as well as with companies and organizations to bring state-of-the-art analytics and big-data research to bear on real-life problems.

Analytics has quickly become a key business strategy for making better decisions. Data streams are growing rapidly in size, speed, and diversity. When you add in high-performance computing capacity and advanced statistical and operations research algorithms, the combination becomes very powerful. The perspective and skills of analytics are in high demand in a wide range of industries, and the need for fundamental research in analytics and big-data related areas is significant.

To improve our ability to analyze, predict, and optimize based on fast-moving and massive-scale data sets, we are working on cutting-edge research in many aspects of the theory, methodology, modeling, and application of modern analytics.